This disclosure relates generally to pulsed radar systems, and more particularly to computationally efficient adaptive radar pulse compression systems. In general, pulsed radar systems transmit a frequency or phase modulated long pulse (or waveform) which after being received is typically match filtered, thereby achieving a range resolution inversely proportional to the bandwidth of the transmitted waveform. The matched filter is the time-reversed complex-conjugate of the transmitted waveform. However, while matched filtering maximizes the target signal-to-noise ratio (SNR) for each range cell, application of the matched filter also results in range sidelobes that occur due to the correlation of the transmitted waveform with delayed versions of itself.
Minimization of range sidelobes has been a topic of intense scrutiny for several years. The prevalent approach to minimizing range sidelobes while maintaining close to the maximum SNR gain of the matched filter has been to employ some form of least squares (LS) estimation (U.S. Pat. No. 5,805,107). Least squares has been shown to provide the most efficient estimator when the additive noise is white. However, LS is not robust in that is does not account for scatterers outside the range cells of interest which can have a deleterious effect on estimation accuracy due to model mismatch.
Recently, an adaptive technique denoted as adaptive pulse compression (APC) was introduced (U.S. Pat. No. 6,940,450) that performs as well as LS yet does not suffer from the robustness problems of LS. However, APC incurs a high computation cost and thus is difficult to implement in a real-time system given current technology.
Thus, there is a need in the art for a computationally efficient adaptive radar pulse compression system.